Watch Live Streaming on:
Beijing (GMT+8): 10:00 p.m., May 13
New York(EST): 10:00 a.m., May 13
Melbourne(GMT+11): 12:00 a.m., May 14
London(GMT): 03:00 p.m., May 13
Interactive structural topology optimization with subjective scoring and drawing systems
Zhi (Albert) Li
Ph.D. candidate at RMIT University | Software developer | Designer
Web: albertlidesign.com
Zhi (Albert) Li is a Ph.D. candidate at the Centre for Innovative Structures and Materials (CISM) at RMIT University, Australia. After completing his Bachelor of Arts degree at Tianjin University in 2018, he embarked on a Ph.D. program in Civil Engineering in 2020. Albert's active research areas include structural optimization, computational design, discrete geometry processing, and digital fabrication.
In addition to his academic achievements, Albert has an impressive background in software development. He contributed to the development of the renowned topology optimization software, Ameba, which was awarded the DigitalFUTURES Coding Award in 2020.
Furthermore, Albert's expertise in computational design has also led to accolades such as the Third Prize in the International 3D Printing and Design Competition for his innovative 3D-printed chair, the Jue Chair.
Abstract
Topology optimization techniques can create efficient and innovative structural designs by redistributing underutilized materials to the most-needed locations. These techniques are typically performed based purely on structural performance without considering factors like aesthetics and other design requirements. Hence, the obtained structural designs may not be suitable for specific practical applications. This study presents a new topology optimization method, SP-BESO, by considering the subjective preferences (SP) of the designer. Here, subjective scoring and drawing systems are introduced into the popular bi-directional evolutionary structural optimization (BESO) technique. The proposed SP-BESO method allows users to iteratively and interactively create topologically different and structurally efficient solutions by explicitly scoring and drawing their subjective preferences. Hence, users do not need to passively accept the optimization results. A user-friendly digital design tool, iBESO, is developed, which contains four optimizers to simultaneously perform the proposed SP-BESO method to assist in the design exploration task. A variety of 2D examples are tested using the iBESO software to demonstrate the effectiveness of the proposed SP-BESO method. It is found that the combination of parameters used in the scoring and drawing systems controls the formation of final structural topologies toward performance-driven or preference-driven designs. The utilization of the proposed SP-BESO method in potential practical applications is also demonstrated.
Host
Wei Wu
Wei Wu is a designer and computational artist with a Master's degree in Design Studies from Harvard University Graduate School of Design. She operates at the intersection of design and emerging technologies, producing work that encompasses robotic installations, interactive media art, and extended reality design.
Comments